化工进展2025，Vol.44Issue(4)：1859-1866,8.DOI:10.16085/j.issn.1000-6613.2024-1503
基于DeepViT和彩虹散射的含颗粒液滴多参数提取方法
Multi-parameter extraction method for particle-containing droplets based on DeepViT and rainbow scattering
摘要
Abstract
This study proposed a multi-parameter extraction method for particle-containing droplets based on the DeepViT deep learning model and rainbow scattering,allowing simultaneous and accurate measurement of the host droplet size and volume fraction of inclusions from the extinction rainbow pattern.The basic composition and implementation methods of the DeepViT model were introduced,including training data preprocessing and network hyperparameters setting.Then,the rainbow optical system and typical measurement signals of particle-containing droplets were demonstrated,and the measurement results of this method under different host droplet sizes and inclusion volume fraction were analyzed and compared with the measurement values of the extinction rainbow method.The relative error of the droplet size measured by this method under the inclusion volume fraction of 0-0.3％was within±0.5％,while the maximum relative error of the extinction rainbow method was about 2％.The maximum absolute error of measuring the inclusion volume fraction under the droplet size of 120-140μm was less than 0.01％.The proposed DeepViT-based method could quickly achieve high-precision in-situ parameter measurements of dynamic heterogeneous droplets such as particle-containing droplets,providing a new idea for the development of particle-containing droplet measurement techniques.关键词
深度学习/彩虹散射/含颗粒液滴/液滴粒径/内含物体积分数/多相流Key words
deep learning/rainbow scattering/particle-containing droplet/droplet size/inclusion volume fraction/multiphase flow分类
信息技术与安全科学引用本文复制引用
黄林滨,李天池,李灿,李宁,翁春生..基于DeepViT和彩虹散射的含颗粒液滴多参数提取方法[J].化工进展,2025,44(4):1859-1866,8.基金项目
国家自然科学基金青年基金(52206221) （52206221）
江苏省自然科学基金(BK20220952) （BK20220952）
江苏省双创博士项目(JSSCBS20210207) （JSSCBS20210207）
中央高校基本科研业务费专项资金项目(30923011028,2023203004). （30923011028,2023203004）
